Reinforcement Learning Engineer

Job Summary

To support innovative solutions in a fully remote environment, the full-time Reinforcement Learning Engineer will design, train, and deploy RL-based systems for high-impact decision-making problems, leveraging modern algorithms and simulation environments.

Key Responsibilities

• Design and implement reinforcement learning solutions for sequential decision-making in real and simulated environments
• Develop and maintain simulation environments for large-scale agent training and optimize training stability
• Collaborate with applied scientists and product teams to identify and evaluate high-value RL use cases

Required Qualifications

• Master's or PhD in Computer Science, Machine Learning, or a related field; or equivalent applied experience
• Six or more years of combined RL research and engineering experience
• Strong proficiency in Python and modern deep learning frameworks
• Hands-on experience with at least one major RL library or in-house RL stack
• Solid understanding of probability, optimization, and the theoretical foundations of RL